Pandas Profiling Report

Dataset statistics

Number of variables	14
Number of observations	88258
Missing cells	361726
Missing cells (%)	29.3%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	7.5 MiB
Average record size in memory	89.0 B

Variable types

Numeric	7
Categorical	2
Boolean	1
Unsupported	3
DateTime	1

Alerts

`Pedido_pendiente_de_suministro_insuficiente` has constant value "True"	Constant
`Fecha_de_pedido` has a high cardinality: 1512 distinct values	High cardinality
`Fecha_de_entrega_esperada` has a high cardinality: 630 distinct values	High cardinality
`ID_de_pedido` is highly correlated with `ID_de_pedido_pendiente`	High correlation
`ID_de_cliente` is highly correlated with `ID_de_persona_de_contacto`	High correlation
`ID_de_persona_de_contacto` is highly correlated with `ID_de_cliente`	High correlation
`ID_de_pedido_pendiente` is highly correlated with `ID_de_pedido`	High correlation
`ID_de_pedido` is highly correlated with `ID_de_pedido_pendiente`	High correlation
`ID_de_cliente` is highly correlated with `ID_de_persona_de_contacto`	High correlation
`ID_de_persona_de_contacto` is highly correlated with `ID_de_cliente`	High correlation
`ID_de_pedido_pendiente` is highly correlated with `ID_de_pedido`	High correlation
`ID_de_pedido` is highly correlated with `ID_de_pedido_pendiente`	High correlation
`ID_de_cliente` is highly correlated with `ID_de_persona_de_contacto`	High correlation
`ID_de_persona_de_contacto` is highly correlated with `ID_de_cliente`	High correlation
`ID_de_pedido_pendiente` is highly correlated with `ID_de_pedido`	High correlation
`ID_de_pedido` is highly correlated with `ID_de_pedido_pendiente`	High correlation
`ID_de_cliente` is highly correlated with `ID_de_persona_de_contacto`	High correlation
`ID_de_persona_de_contacto` is highly correlated with `ID_de_cliente`	High correlation
`ID_de_pedido_pendiente` is highly correlated with `ID_de_pedido`	High correlation
`Seleccionado_por_ID_de_persona` has 13570 (15.4%) missing values	Missing
`ID_de_pedido_pendiente` has 79035 (89.5%) missing values	Missing
`Comentarios` has 88258 (100.0%) missing values	Missing
`Instrucciones_de_entrega` has 88258 (100.0%) missing values	Missing
`Comentarios_internos` has 88258 (100.0%) missing values	Missing
`Seleccion_completada_cuando` has 4347 (4.9%) missing values	Missing
`ID_de_pedido` is uniformly distributed	Uniform
`Comentarios` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`Instrucciones_de_entrega` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`Comentarios_internos` is an unsupported type, check if it needs cleaning or further analysis	Unsupported

Reproduction

Analysis started	2024-06-29 17:59:38.022919
Analysis finished	2024-06-29 18:03:10.332734
Duration	3 minutes and 32.31 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

ID_de_pedido
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct	54145
Distinct (%)	61.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	46547.75124

Minimum	19443
Maximum	73595
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	344.9 KiB

Quantile statistics

Minimum	19443
5-th percentile	22149
Q1	33072
median	46546
Q3	60071
95-th percentile	70898.15
Maximum	73595
Range	54152
Interquartile range (IQR)	26999

Descriptive statistics

Standard deviation	15608.64492
Coefficient of variation (CV)	0.3353254348
Kurtosis	-1.196202414
Mean	46547.75124
Median Absolute Deviation (MAD)	13502
Skewness	-0.0007785763955
Sum	4108211429
Variance	243629796.3
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
42245	3	< 0.1%
50881	3	< 0.1%
63970	3	< 0.1%
53676	3	< 0.1%
25850	3	< 0.1%
72992	3	< 0.1%
53083	3	< 0.1%
47875	3	< 0.1%
34251	3	< 0.1%
62677	3	< 0.1%
Other values (54135)	88228	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
19443	1	< 0.1%
19444	1	< 0.1%
19445	1	< 0.1%
19446	1	< 0.1%
19447	1	< 0.1%
19448	1	< 0.1%
19449	2	< 0.1%
19450	1	< 0.1%
19451	2	< 0.1%
19452	1	< 0.1%

Value	Count	Frequency (%)
73595	2	< 0.1%
73594	2	< 0.1%
73593	2	< 0.1%
73592	2	< 0.1%
73591	3	< 0.1%
73590	1	< 0.1%
73589	1	< 0.1%
73588	2	< 0.1%
73587	1	< 0.1%
73586	2	< 0.1%

ID_de_cliente
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	663
Distinct (%)	0.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	534.5820549

Minimum	1
Maximum	1061
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	344.9 KiB

Quantile statistics

Minimum	1
5-th percentile	33
Q1	162
median	521
Q3	883
95-th percentile	1012
Maximum	1061
Range	1060
Interquartile range (IQR)	721

Descriptive statistics

Standard deviation	345.8665216
Coefficient of variation (CV)	0.646984908
Kurtosis	-1.42979991
Mean	534.5820549
Median Absolute Deviation (MAD)	360
Skewness	-0.06455180167
Sum	47181143
Variance	119623.6508
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
472	182	0.2%
548	175	0.2%
183	174	0.2%
70	173	0.2%
964	173	0.2%
405	173	0.2%
804	172	0.2%
67	172	0.2%
169	171	0.2%
118	170	0.2%
Other values (653)	86523	98.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	159	0.2%
2	152	0.2%
3	151	0.2%
4	117	0.1%
5	149	0.2%
6	129	0.1%
7	134	0.2%
8	120	0.1%
9	163	0.2%
10	157	0.2%

Value	Count	Frequency (%)
1061	16	< 0.1%
1060	6	< 0.1%
1059	11	< 0.1%
1058	20	< 0.1%
1057	26	< 0.1%
1056	21	< 0.1%
1055	45	0.1%
1054	47	0.1%
1053	40	< 0.1%
1052	49	0.1%

ID_de_vendedor
Real number (ℝ_≥0)

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	10.42955879

Minimum	2
Maximum	20
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	344.9 KiB

Quantile statistics

Minimum	2
5-th percentile	2
Q1	6
median	13
Q3	15
95-th percentile	20
Maximum	20
Range	18
Interquartile range (IQR)	9

Descriptive statistics

Standard deviation	5.712593445
Coefficient of variation (CV)	0.5477310745
Kurtosis	-1.251630752
Mean	10.42955879
Median Absolute Deviation (MAD)	5
Skewness	0.03193206922
Sum	920492
Variance	32.63372386
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
16	9008	10.2%
15	8924	10.1%
13	8921	10.1%
2	8872	10.1%
14	8851	10.0%
6	8806	10.0%
20	8779	9.9%
3	8728	9.9%
8	8690	9.8%
7	8679	9.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	8872	10.1%
3	8728	9.9%
6	8806	10.0%
7	8679	9.8%
8	8690	9.8%
13	8921	10.1%
14	8851	10.0%
15	8924	10.1%
16	9008	10.2%
20	8779	9.9%

Value	Count	Frequency (%)
20	8779	9.9%
16	9008	10.2%
15	8924	10.1%
14	8851	10.0%
13	8921	10.1%
8	8690	9.8%
7	8679	9.8%
6	8806	10.0%
3	8728	9.9%
2	8872	10.1%

Seleccionado_por_ID_de_persona
Real number (ℝ_≥0)

MISSING

Distinct	19
Distinct (%)	< 0.1%
Missing	13570
Missing (%)	15.4%
Infinite	0
Infinite (%)	0.0%
Mean	10.95699443

Minimum	2
Maximum	20
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	689.6 KiB

Quantile statistics

Minimum	2
5-th percentile	3
Q1	6
median	11
Q3	16
95-th percentile	19
Maximum	20
Range	18
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	5.460278195
Coefficient of variation (CV)	0.4983372247
Kurtosis	-1.233665779
Mean	10.95699443
Median Absolute Deviation (MAD)	5
Skewness	0.01761212988
Sum	818356
Variance	29.81463797
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=19)

Value	Count	Frequency (%)
18	5022	5.7%
8	4851	5.5%
7	4575	5.2%
3	4469	5.1%
17	4375	5.0%
4	4276	4.8%
10	4072	4.6%
9	4000	4.5%
6	3862	4.4%
14	3786	4.3%
Other values (9)	31400	35.6%
(Missing)	13570	15.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	3448	3.9%
3	4469	5.1%
4	4276	4.8%
5	3022	3.4%
6	3862	4.4%
7	4575	5.2%
8	4851	5.5%
9	4000	4.5%
10	4072	4.6%
11	3437	3.9%

Value	Count	Frequency (%)
20	3348	3.8%
19	3603	4.1%
18	5022	5.7%
17	4375	5.0%
16	3716	4.2%
15	3734	4.2%
14	3786	4.3%
13	3545	4.0%
12	3547	4.0%
11	3437	3.9%

ID_de_persona_de_contacto
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	663
Distinct (%)	0.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2234.913606

Minimum	1001
Maximum	3261
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	344.9 KiB

Quantile statistics

Minimum	1001
5-th percentile	1065
Q1	1323
median	2241
Q3	3083
95-th percentile	3212
Maximum	3261
Range	2260
Interquartile range (IQR)	1760

Descriptive statistics

Standard deviation	800.280987
Coefficient of variation (CV)	0.3580813974
Kurtosis	-1.475072091
Mean	2234.913606
Median Absolute Deviation (MAD)	868
Skewness	-0.1753608184
Sum	197249005
Variance	640449.6582
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2143	182	0.2%
2295	175	0.2%
1365	174	0.2%
1139	173	0.2%
3164	173	0.2%
2009	173	0.2%
3004	172	0.2%
1133	172	0.2%
1337	171	0.2%
1235	170	0.2%
Other values (653)	86523	98.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1001	159	0.2%
1003	152	0.2%
1005	151	0.2%
1007	117	0.1%
1009	149	0.2%
1011	129	0.1%
1013	134	0.2%
1015	120	0.1%
1017	163	0.2%
1019	157	0.2%

Value	Count	Frequency (%)
3261	16	< 0.1%
3260	6	< 0.1%
3259	11	< 0.1%
3258	20	< 0.1%
3257	26	< 0.1%
3256	21	< 0.1%
3255	45	0.1%
3254	47	0.1%
3253	40	< 0.1%
3252	49	0.1%

ID_de_pedido_pendiente
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	5666
Distinct (%)	61.4%
Missing	79035
Missing (%)	89.5%
Infinite	0
Infinite (%)	0.0%
Mean	46971.11081

Minimum	19532
Maximum	73595
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	689.6 KiB

Quantile statistics

Minimum	19532
5-th percentile	22430.1
Q1	33756.5
median	47272
Q3	60249.5
95-th percentile	71019.9
Maximum	73595
Range	54063
Interquartile range (IQR)	26493

Descriptive statistics

Standard deviation	15466.66876
Coefficient of variation (CV)	0.3292804554
Kurtosis	-1.180305062
Mean	46971.11081
Median Absolute Deviation (MAD)	13273
Skewness	-0.02223146013
Sum	433214555
Variance	239217842.5
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
27630	3	< 0.1%
71586	3	< 0.1%
21967	3	< 0.1%
26320	3	< 0.1%
71212	3	< 0.1%
43244	3	< 0.1%
39370	3	< 0.1%
52209	3	< 0.1%
72277	3	< 0.1%
64593	3	< 0.1%
Other values (5656)	9193	10.4%
(Missing)	79035	89.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
19532	3	< 0.1%
19533	1	< 0.1%
19534	1	< 0.1%
19535	2	< 0.1%
19536	1	< 0.1%
19537	2	< 0.1%
19538	2	< 0.1%
19539	2	< 0.1%
19590	2	< 0.1%
19591	2	< 0.1%

Value	Count	Frequency (%)
73595	3	< 0.1%
73594	2	< 0.1%
73593	2	< 0.1%
73592	2	< 0.1%
73591	2	< 0.1%
73590	1	< 0.1%
73589	1	< 0.1%
73588	1	< 0.1%
73587	1	< 0.1%
73505	2	< 0.1%

Fecha_de_pedido
Categorical

HIGH CARDINALITY

Distinct	1512
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	689.6 KiB

2015-02-03	163
2016-01-06	163
2015-10-19	162
2016-03-23	159
2015-07-06	158
Other values (1507)	87453

Length

Max length	11
Median length	10
Mean length	10.22700492
Min length	10

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Mar 05,2015
2nd row	Mar 24,2015
3rd row	Mar 18,2014
4th row	Apr 21,2015
5th row	Nov 11,2014

Common Values

Value	Count	Frequency (%)
2015-02-03	163	0.2%
2016-01-06	163	0.2%
2015-10-19	162	0.2%
2016-03-23	159	0.2%
2015-07-06	158	0.2%
2015-11-24	158	0.2%
2016-04-28	155	0.2%
2016-05-04	155	0.2%
2015-02-27	155	0.2%
2015-07-30	154	0.2%
Other values (1502)	86676	98.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
may	2187	2.0%
apr	2148	2.0%
jan	2108	1.9%
mar	1951	1.8%
feb	1858	1.7%
jul	1576	1.5%
oct	1467	1.4%
jun	1420	1.3%
dec	1412	1.3%
sep	1357	1.3%
Other values (851)	90809	83.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Fecha_de_entrega_esperada
Categorical

HIGH CARDINALITY

Distinct	630
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	689.6 KiB

2015-03-02	287
2016-05-16	283
2016-01-11	266
2014-04-28	265
2015-06-08	264
Other values (625)	86893

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2015-03-06
2nd row	2015-03-25
3rd row	2014-03-19
4th row	2015-04-22
5th row	2014-11-12

Common Values

Value	Count	Frequency (%)
2015-03-02	287	0.3%
2016-05-16	283	0.3%
2016-01-11	266	0.3%
2014-04-28	265	0.3%
2015-06-08	264	0.3%
2015-06-01	263	0.3%
2015-09-14	263	0.3%
2015-04-06	262	0.3%
2016-04-11	259	0.3%
2015-03-30	258	0.3%
Other values (620)	85588	97.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
2015-03-02	287	0.3%
2016-05-16	283	0.3%
2016-01-11	266	0.3%
2014-04-28	265	0.3%
2015-06-08	264	0.3%
2015-06-01	263	0.3%
2015-09-14	263	0.3%
2015-04-06	262	0.3%
2016-04-11	259	0.3%
2015-03-30	258	0.3%
Other values (620)	85588	97.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Numero_de_pedido_de_compra_del_cliente
Real number (ℝ_≥0)

Distinct	9926
Distinct (%)	11.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	14993.60438

Minimum	10001
Maximum	20000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	689.6 KiB

Quantile statistics

Minimum	10001
5-th percentile	10505
Q1	12493
median	14995
Q3	17496
95-th percentile	19492
Maximum	20000
Range	9999
Interquartile range (IQR)	5003

Descriptive statistics

Standard deviation	2882.03311
Coefficient of variation (CV)	0.1922174974
Kurtosis	-1.198478346
Mean	14993.60438
Median Absolute Deviation (MAD)	2501.5
Skewness	0.001300334427
Sum	1323305535
Variance	8306114.85
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
15358	32	< 0.1%
19786	30	< 0.1%
10776	29	< 0.1%
15758	29	< 0.1%
16651	28	< 0.1%
14856	28	< 0.1%
12650	27	< 0.1%
19885	27	< 0.1%
18144	26	< 0.1%
11658	26	< 0.1%
Other values (9916)	87976	99.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
10001	7	< 0.1%
10002	20	< 0.1%
10003	20	< 0.1%
10004	15	< 0.1%
10005	15	< 0.1%
10006	6	< 0.1%
10007	22	< 0.1%
10008	4	< 0.1%
10009	21	< 0.1%
10010	4	< 0.1%

Value	Count	Frequency (%)
20000	9	< 0.1%
19999	1	< 0.1%
19998	10	< 0.1%
19997	4	< 0.1%
19996	16	< 0.1%
19995	10	< 0.1%
19994	9	< 0.1%
19993	12	< 0.1%
19992	7	< 0.1%
19991	8	< 0.1%

Pedido_pendiente_de_suministro_insuficiente
Boolean

CONSTANT
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	86.3 KiB

True	88258

Common Values
Chart

Value	Count	Frequency (%)
True	88258	100.0%

Comentarios
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	88258
Missing (%)	100.0%
Memory size	689.6 KiB

Instrucciones_de_entrega
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	88258
Missing (%)	100.0%
Memory size	689.6 KiB

Comentarios_internos
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	88258
Missing (%)	100.0%
Memory size	689.6 KiB

Seleccion_completada_cuando
Date

MISSING

Distinct	1506
Distinct (%)	1.8%
Missing	4347
Missing (%)	4.9%
Memory size	689.6 KiB

Minimum	2014-01-01 11:00:00
Maximum	2016-05-31 12:00:00

Histogram

Histogram with fixed size bins (bins=50)

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	ID_de_pedido	ID_de_cliente	ID_de_vendedor	Seleccionado_por_ID_de_persona	ID_de_persona_de_contacto	ID_de_pedido_pendiente	Fecha_de_pedido	Fecha_de_entrega_esperada	Numero_de_pedido_de_compra_del_cliente	Pedido_pendiente_de_suministro_insuficiente	Comentarios	Instrucciones_de_entrega	Comentarios_internos	Seleccion_completada_cuando
0	44495	139	6	18.0	1277	NaN	Mar 05,2015	2015-03-06	13118	True	None	None	None	2015-03-06 11:00:00
1	45625	892	15	17.0	3092	NaN	Mar 24,2015	2015-03-25	11303	True	None	None	None	2015-03-24 11:00:00
2	23645	542	8	9.0	2283	NaN	Mar 18,2014	2014-03-19	18340	True	None	None	None	2014-03-18 11:00:00
3	47505	924	15	4.0	3124	NaN	Apr 21,2015	2015-04-22	18645	True	None	None	None	2015-04-21 11:00:00
4	37755	43	7	10.0	1085	NaN	Nov 11,2014	2014-11-12	16259	True	None	None	None	2014-11-11 11:00:00
5	36114	54	3	10.0	1107	NaN	Oct 16,2014	2014-10-17	17861	True	None	None	None	2014-10-16 11:00:00
6	48423	956	3	9.0	3156	NaN	May 04,2015	2015-05-05	19616	True	None	None	None	2015-09-24 11:00:00
7	38465	1028	16	12.0	3228	NaN	Nov 24,2014	2014-11-25	18936	True	None	None	None	2014-11-24 11:00:00
8	48651	39	2	NaN	1077	NaN	May 07,2015	2015-05-08	13944	True	None	None	None	NaT
9	34080	25	8	3.0	1049	NaN	Sep 10,2014	2014-09-11	11079	True	None	None	None	2014-09-10 11:00:00

Last rows

	ID_de_pedido	ID_de_cliente	ID_de_vendedor	Seleccionado_por_ID_de_persona	ID_de_persona_de_contacto	ID_de_pedido_pendiente	Fecha_de_pedido	Fecha_de_entrega_esperada	Numero_de_pedido_de_compra_del_cliente	Pedido_pendiente_de_suministro_insuficiente	Comentarios	Instrucciones_de_entrega	Comentarios_internos	Seleccion_completada_cuando
88248	63342	894	3	NaN	3094	63377.0	2015-12-22	2015-12-23	10582	True	None	None	None	2015-12-22 12:00:00
88249	37851	94	16	3.0	1187	NaN	2014-11-13	2014-11-14	12114	True	None	None	None	2014-11-13 11:00:00
88250	70517	830	16	8.0	3030	NaN	2016-04-15	2016-04-18	15939	True	None	None	None	2016-04-15 11:00:00
88251	31919	575	2	11.0	2349	NaN	2014-08-01	2014-08-04	11877	True	None	None	None	2014-08-01 11:00:00
88252	58045	122	6	NaN	1243	58116.0	2015-09-29	2015-09-30	18016	True	None	None	None	2015-09-29 12:00:00
88253	71539	897	14	18.0	3097	NaN	2016-04-30	2016-05-02	18811	True	None	None	None	2016-04-30 11:00:00
88254	47453	981	3	4.0	3181	NaN	2015-04-21	2015-04-22	19539	True	None	None	None	2015-04-21 11:00:00
88255	58181	869	3	20.0	3069	NaN	2015-09-30	2015-10-01	19442	True	None	None	None	2015-09-30 11:00:00
88256	57068	892	6	19.0	3092	NaN	2015-09-14	2015-09-15	19090	True	None	None	None	2015-09-14 11:00:00
88257	34340	70	2	NaN	1139	NaN	2014-09-15	2014-09-16	19896	True	None	None	None	NaT

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Spearman's ρ

Pearson's r

Kendall's τ

Phik (φk)

Missing values

Sample

First rows

Last rows